Inference and learning in fuzzy bayesian networks

J. Baldwin, E. D. Tomaso
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引用次数: 27

Abstract

This paper deals with the development of a theory on bayesian networks. It proposes a modified algorithm for solving knowledge querying and information updating, when dealing with continuous variables and with probabilistic and uncertain instantiations. Fuzzy sets are used to rewrite the information contained in a database in order to reduce the complexity of the automatic learning of a bayesian net from data.
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模糊贝叶斯网络中的推理与学习
本文讨论了贝叶斯网络理论的发展。针对连续变量、概率和不确定实例化问题,提出了一种改进的知识查询和信息更新算法。模糊集用于重写数据库中包含的信息,以降低贝叶斯网络从数据中自动学习的复杂性。
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